Victoria Arenas-Ramos;Victor Pallares-Lopez;Rafael Real-Calvo;Miguel Gonzalez-Redondo;Isabel Santiago-Chiquero
{"title":"基于自制相量测量单元的光伏电站高精度监测系统的实现与特性研究","authors":"Victoria Arenas-Ramos;Victor Pallares-Lopez;Rafael Real-Calvo;Miguel Gonzalez-Redondo;Isabel Santiago-Chiquero","doi":"10.1109/JSEN.2025.3598820","DOIUrl":null,"url":null,"abstract":"The increasing integration of photovoltaic (PV) plants into the power grid presents an ongoing challenge to prevent the instability caused by atmospheric conditions from affecting the power distribution network. To adequately control the network and implement such techniques, monitoring has been considerably improved in recent years. Due to the vast number of measurements generated, efficient management of this data has become a significant challenge. This article outlines a procedure used for simultaneously storing synchronized measured data from phasor measurement units (PMUs) and PMU-like data from acquisition data acquisition (DAQ) devices through self-made extended-PMUs (ePMUs). Throughout this article, a communication and storage environment that complies with the IEEE C37.118.2 standard for Synchrophasor Data Transfer for Power Systems will be characterized based on criteria established in the IEC 61850-90-5 standard for power utility automation. In addition, it justifies the chosen storage method through a comprehensive study of data volume and reading accessibility. The procedure and the ePMUs have been experimentally validated in field tests in two grid-connected PV plants. The procedure was proven to be valid for quasi-real-time applications for data registered and sent both in a local area network (LAN) and a wide area network (WAN). Thanks to the dataframes synchronize up to the millisecond, data can also be studied offline seamlessly.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 19","pages":"37383-37393"},"PeriodicalIF":4.3000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11131518","citationCount":"0","resultStr":"{\"title\":\"Implementation and Characterization of a High-Precision Monitoring System for Photovoltaic Power Plants Using Self-Made Phasor Measurement Units\",\"authors\":\"Victoria Arenas-Ramos;Victor Pallares-Lopez;Rafael Real-Calvo;Miguel Gonzalez-Redondo;Isabel Santiago-Chiquero\",\"doi\":\"10.1109/JSEN.2025.3598820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing integration of photovoltaic (PV) plants into the power grid presents an ongoing challenge to prevent the instability caused by atmospheric conditions from affecting the power distribution network. To adequately control the network and implement such techniques, monitoring has been considerably improved in recent years. Due to the vast number of measurements generated, efficient management of this data has become a significant challenge. This article outlines a procedure used for simultaneously storing synchronized measured data from phasor measurement units (PMUs) and PMU-like data from acquisition data acquisition (DAQ) devices through self-made extended-PMUs (ePMUs). Throughout this article, a communication and storage environment that complies with the IEEE C37.118.2 standard for Synchrophasor Data Transfer for Power Systems will be characterized based on criteria established in the IEC 61850-90-5 standard for power utility automation. In addition, it justifies the chosen storage method through a comprehensive study of data volume and reading accessibility. The procedure and the ePMUs have been experimentally validated in field tests in two grid-connected PV plants. The procedure was proven to be valid for quasi-real-time applications for data registered and sent both in a local area network (LAN) and a wide area network (WAN). 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Implementation and Characterization of a High-Precision Monitoring System for Photovoltaic Power Plants Using Self-Made Phasor Measurement Units
The increasing integration of photovoltaic (PV) plants into the power grid presents an ongoing challenge to prevent the instability caused by atmospheric conditions from affecting the power distribution network. To adequately control the network and implement such techniques, monitoring has been considerably improved in recent years. Due to the vast number of measurements generated, efficient management of this data has become a significant challenge. This article outlines a procedure used for simultaneously storing synchronized measured data from phasor measurement units (PMUs) and PMU-like data from acquisition data acquisition (DAQ) devices through self-made extended-PMUs (ePMUs). Throughout this article, a communication and storage environment that complies with the IEEE C37.118.2 standard for Synchrophasor Data Transfer for Power Systems will be characterized based on criteria established in the IEC 61850-90-5 standard for power utility automation. In addition, it justifies the chosen storage method through a comprehensive study of data volume and reading accessibility. The procedure and the ePMUs have been experimentally validated in field tests in two grid-connected PV plants. The procedure was proven to be valid for quasi-real-time applications for data registered and sent both in a local area network (LAN) and a wide area network (WAN). Thanks to the dataframes synchronize up to the millisecond, data can also be studied offline seamlessly.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice